Accelerating AI model serving with the Modular AI Engine

The Modular AI Engine has been introduced as a fast and versatile AI inference engine providing significant usability, portability, and performance improvements for AI frameworks like PyTorch and TensorFlow. Integrated into existing serving solutions such as NVIDIA's Triton Inference Server and TensorFlow Serving, it offers seamless deployment with features like dynamic batching and concurrency. Performance testing on various hardware, including AWS Graviton2, AMD EPYC, and Intel Skylake, demonstrated that the Modular AI Engine achieves superior throughput and lower latency compared to TensorFlow and PyTorch. By maintaining consistent default settings, the engine improves upon common models like BERT-base in production environments, highlighting its ability to scale efficiently across multiple architectures. As part of its ongoing development, Modular is enhancing its platform for performance-sensitive AI models and invites users to explore more details on its Performance Dashboard and stay updated through its newsletter.